As a Data Analytics Engineer at Stori, you will leverage your analytical and technical expertise
to support our Deposits functions. Your role will be critical in ensuring data accuracy,
compliance, and the generation of reports and reconciliations processes. On any given day, you
will be challenged on three types of work – Innovation, Business Intelligence, and Data
Management • A bachelor's degree or foreign equivalent in Engineering, Science, Operations Research,
Information Technology, Statistics, Mathematics, Economics, Finance, Analytics, or a related
quantitative analytical field.
• Basic skills in SQL and Python for data manipulation and analysis.
• Proven interpersonal, collaboration, diplomatic, influencing, planning, and organizational skills.
• Consistently demonstrate clear and concise written and verbal communication.
• Proven ability to effectively use complex analytical, interpretive, and problem-solving
techniques.
• Demonstrated ability to work under pressure and to meet tight deadlines with proactive,
decisiveness, and flexibility.
• English B1 or above.
• 2 or more years of experience in quantitative and qualitative analysis using SQL or Python.
• 2 or more years of working experience in data analytics.
• Deep understanding of credit product operations (credit cards, loans, asset financing, etc.).
• Understanding of financial regulations and accounting principles, especially within the fintech
industry.
• Experience with regulatory and compliance reporting in a financial services context. Innovation
• Develop and enhance data-driven solutions for accounting processes, including the
automation of marketing reporting to improve accuracy and efficiency.
• Use Open Source/Digital technologies to mine complex, voluminous, and different varieties of
data sources and platforms.
• Build well-managed data solutions, tools, and capabilities to enable self-service frameworks for
data consumers.
• Demonstrate the ability to explore and quickly grasp new technologies to progress varied
initiatives.
Business Intelligence
• Collaborate closely with teams to launch new products or features, ensuring they are aligned
with acquisition objectives.
• Partner with the business to provide consultancy and translate the business needs to design
and develop tools, techniques, metrics, and dashboards for insights and data visualization.
• Drive analysis that provides meaningful insights on business strategies.
Data Management
● Drive an understanding and adherence to the principles of data quality management,
including metadata, lineage, and business definitions.
● Work with business teams to understand their needs and translate them into
technical requirements.
● Work collaboratively with appropriate Tech teams to manage security mechanisms
and data access governance.
● Build and execute tools to monitor and report on data quality.